The present disclosure is related to video coding and, more particularly, to coding the movement of a head from a sequence of images.
As is well-known, motion estimation is a common or frequently encountered problem in digital video processing. A number of approaches are known and have been employed. One approach, for example, identifies the features located on the object and tracks the features from frame to frame, as described for example in “Two-View Facial Movement Estimation” by H. Li and R. Forchheimer, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 4, No. 3, pp. 276–287, June, 1994. In this approach, the features are tracked from the two-dimensional correspondence between successive frames. From this correspondence, the three-dimensional motion parameters are estimated. Another approach estimates the motion parameters from an optical flow and affine motion model. See, for example, “Analysis and Synthesis of Facial Image Sequences in Model-Based Coding,” by C. S. Choi, K. Aizawa, H. Harashima and T. Takeve, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 4, No. 3, pp. 257–275, June, 1994. This optical flow approach estimates the motion parameters without establishing a two-dimensional correspondence. This latter approach, therefore, tends to be more robust and accurate, but imposes a computational load that is heavier typically. A need, therefore, exists for an approach that is more accurate then the two-dimensional correspondence approach, but that is computationally less burdensome than the optical flow and affine motion model.